A Framework on Ontology Based Classification and Clustering for Grouping Research Proposals
نویسنده
چکیده
The Research project proposals selection is an challenging task in organizations and companies. When large numbers of research proposals are collected then research Project Selection is a remarkable in all Research funding and Government agencies. The process of Assignment and Selection are unproblematic. The number of proposal submissions are very less. But with mounting in numbers both assignment and Selection processes will become complicated. The traditional methodologies, Proposal Grouping and Experts grouping experts are done keywords or manually. which yield inefficient experiment results. In present days methodologies are Ontology based Text Mining Method has been used to cluster Proposals based on their likeness in research area by means of Research Ontology method. Where as Reviewers grouping and proposal assignment to experts is still not precise and it is done manually. In this proposed paper proposes Ontology based Text Mining Method to cluster reviewers based on their specialism and overcome the Ontology Mapping Problem to allocate proposals to relevant reviewers analytically. This methodology an effective way for research project selection with escalating proposals and reviewers. Keywords—Ontology, Clustering, Conceptbased analysis, Research Project Selection, Genetic Algorithm, Grouping process, Ontology Matching.
منابع مشابه
Research Proposal Selection Using Clustering and Ontology Based Text Mining Method
Selection of research project is a very important process for government and for private research funding agency. When the agency or research institution received lots of research proposals then according to the similarity these can be grouped in research area and then assigned to the respective experts or guide for review. This approach of grouping the research proposal based on keywords and m...
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